{"id":"W6894238803","doi":"10.5281/zenodo.7918058","title":"Amblyaspis tatika Awad & Krogmann & Talamas 2023, comb. nov.","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Clade; Holotype; DNA barcoding; Tree (set theory); Phylogenetic tree","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001134337,0.0007725548,0.0003535373,0.001743897,0.0015709,0.0005355002,0.0005383719,0.0005820221,0.01045477],"category_scores_gemma":[0.0004471856,0.000218702,0.0003261092,0.001281426,0.0005385765,0.0009700924,0.0007049248,0.0008769793,0.004085298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005977582,"about_ca_system_score_gemma":0.0006232692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009273198,"about_ca_topic_score_gemma":0.01701363,"domain_scores_codex":[0.9998282,0.000009456703,0.00002056435,0.0000588197,0.00005911178,0.00002370835],"domain_scores_gemma":[0.9998481,0.00002660207,0.00004672814,0.00001955729,0.00003456908,0.00002438767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001150123,0.0001582391,0.07506827,0.001412438,0.0003834595,0.007238062,0.002438427,0.002586746,0.1265393,0.006033692,0.0330948,0.7438965],"study_design_scores_gemma":[0.0002124391,0.0003488181,0.5310948,0.0009629558,0.0005621869,0.02740341,0.003061918,0.001877323,0.009627601,0.002570961,0.4221844,0.00009305123],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7081458,0.01918685,0.01613816,0.0009841803,0.001807948,0.001019846,0.01731957,0.0009282213,0.2344694],"genre_scores_gemma":[0.9448994,0.006262066,0.01281241,0.0005492611,0.0002208466,0.0003372181,0.01050605,0.00008403041,0.02432867],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01045477,"threshold_uncertainty_score":0.03497469,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03451972849290631,"score_gpt":0.2578404682137789,"score_spread":0.2233207397208726,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}